Selection and Validation of Housekeeping Genes for RT-qPCR Normalization Studies Involving Potato Plants Infected with PVY

Accurate data normalization is essential for reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) studies. However, studies on suitable reference genes for gene expression analysis remain scarce. With RT-qPCR offering increased sensitivity, reproducibility, and a wide dynamic range, the need for a robust internal control gene for normalization has become more stringent. To aid in quantifying gene expressions in potato plants infected with potato virus (PVY), we investigated the expression profiles of five candidate housekeeping genes in potato plants: ACT (β-actin), TUB (β-tubulin), EF1α (Elongation factor 1-alpha), GAPDH (glyceraldehyde 3-phosphate dehydrogenase), and RPL19 (ribosomal protein L19), across different strains of PVY (PVYO, PVYN, PVYNTN, and PVYN-Wi). Ct values from biological and technical replicates were averaged using four different algorithms – geNorm, NormFinder, Comparative ΔCt, and BestKeeper – and a comprehensive analysis using an online software, RefFinder. Our findings identified TUB and EF1α as the most stable reference genes for PVYO, TUB and GAPDH for PVYN, ACT and RPL19 for PVYNTN, and EF1α and TUB for PVYN-Wi. This research sheds light on the understanding of reference gene stability in potato plants infected with various PVY strains and provides foundational support for standardized RT-qPCR analyses on plants infected with this virus.

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Journal
ACS Agricultural Science & Technology
Published
2026-02-04
DOI
https://doi.org/10.1021/acsagscitech.5c00941
Primary Topic
Molecular Biology Techniques and Applications
Type
article
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article

Selection and Validation of Housekeeping Genes for RT-qPCR Normalization Studies Involving Potato Plants Infected with PVY

Jarlan Lucas Santos Silva, Washington da Silva, J. C. Milagres, Aida Feng et al.
ACS Agricultural Science & Technology
Molecular Biology Techniques and Applications
article

Selection and Validation of Housekeeping Genes for RT-qPCR Normalization Studies Involving Potato Plants Infected with PVY

Jarlan Lucas Santos Silva, Washington da Silva, J. C. Milagres, Aida Feng, Cleverson Diniz Teixeira de Freitas, José Joedson Lima Silva
article en

Abstract

Accurate data normalization is essential for reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) studies. However, studies on suitable reference genes for gene expression analysis remain scarce. With RT-qPCR offering increased sensitivity, reproducibility, and a wide dynamic range, the need for a robust internal control gene for normalization has become more stringent. To aid in quantifying gene expressions in potato plants infected with potato virus (PVY), we investigated the expression profiles of five candidate housekeeping genes in potato plants: ACT (β-actin), TUB (β-tubulin), EF1α (Elongation factor 1-alpha), GAPDH (glyceraldehyde 3-phosphate dehydrogenase), and RPL19 (ribosomal protein L19), across different strains of PVY (PVYO, PVYN, PVYNTN, and PVYN-Wi). Ct values from biological and technical replicates were averaged using four different algorithms – geNorm, NormFinder, Comparative ΔCt, and BestKeeper – and a comprehensive analysis using an online software, RefFinder. Our findings identified TUB and EF1α as the most stable reference genes for PVYO, TUB and GAPDH for PVYN, ACT and RPL19 for PVYNTN, and EF1α and TUB for PVYN-Wi. This research sheds light on the understanding of reference gene stability in potato plants infected with various PVY strains and provides foundational support for standardized RT-qPCR analyses on plants infected with this virus.

ACS Agricultural Science & TechnologyVol. 6(2)
Universidade Federal de Viçosa (BR), Universidade Federal do Ceará (BR), Connecticut Agricultural Experiment Station (US), Yale University (US), Instituto Florestal (BR), Flint Institute Of Arts (US), Instituto de Biotecnología y Biología Molecular (AR), Universidade Federal Rural do Semi-Árido (BR)
Openalex Percentile: Top 67%
Molecular Biology Techniques and Applications
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